textnets 0.5.3

Automated text analysis with networks

textnets represents collections of texts as networks of documents and words. This provides novel possibilities for the visualization and analysis of texts.

Network of U.S. Senators and words used in their official statements following the acquittal vote in the 2020 Senate impeachment trial (source).

This is a Python implementation of Chris Bail’s textnets package for R. It is free software under the terms of the GNU General Public License v3.

The idea underlying textnets is presented in this paper:

Christopher A. Bail, “Combining natural language processing and network analysis to examine how advocacy organizations stimulate conversation on social media,” Proceedings of the National Academy of Sciences of the United States of America 113, no. 42 (2016), 11823–11828, doi:10.1073/pnas.1607151113.

Features

textnets builds on the state-of-the-art library spaCy for natural-language processing and igraph for network analysis. It uses the Leiden algorithm for community detection, which is able to perform community detection on the bipartite (word–group) network.

textnets seamlessly integrates with Python’s excellent scientific stack. That means that you can use textnets in Jupyter notebooks to analyze and visualize your data!

textnets is easily installable using the conda and pip package managers. It requires Python 3.7 or higher.

Read the documentation to learn more about the package’s features.

Citation

Using textnets in a scholarly publication? Please cite this paper:

@article{Boy2020,
  author   = {John D. Boy},
  title    = {textnets},
  subtitle = {A {P}ython Package for Text Analysis with Networks},
  journal  = {Journal of Open Source Software},
  volume   = {5},
  number   = {54},
  pages    = {2594},
  year     = {2020},
  doi      = {10.21105/joss.02594},
}

Learn More

Documentation	https://textnets.readthedocs.io/
Repository	https://github.com/jboynyc/textnets
Issues & Ideas	https://github.com/jboynyc/textnets/issues
Conda-Forge	https://anaconda.org/conda-forge/textnets
PyPI	https://pypi.org/project/textnets/
DOI	10.21105/joss.02594
Archive	10.5281/zenodo.3866676